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Putting IBCS in practice

IBCS or International Business Communication Standards is a set of best practices for data visualisation aiming to make visualisations immediately relatable and understandable. With IBCS, you also try to maximise information density whilst avoiding clutter and distractions from the message you're trying to convey.


Here, I'm going to take an example of information I found interesting but cluttered and confusing.

I will then try to render the same info again according to IBCS.

 

Let's take the example of this data visualisation:

It provides a fairly useful information: it's fairly obvious that the top 3 websites are Google, Youtube and Facebook, but then...


Top 50 websites in terms of what ? Clicks ? Users ? Average monthly or yearly ?

What is the source of data ?


Why the choice of bubbles ? It's very difficult for the brain to assess how much a bubble is bigger or smaller than an other one. Can you easily tell that Instagram is double of Whatsapp ? To understand that, you need to read the number here, so the bubble adds nothing.


How are the bubbles ordered ? The top 3 are in the middle, but then on the left we have #16 followed by #21. #15 is on the right. What's happening here ?


What about the colour legend ? Is it related to the website category (table on the top left) ? But all the categories are in grey, so it's difficult to relate immediately a colour to a category. To me, Pornhub would bit in the Adult category, but then Walmart has the same colour coding, so is it classified as Adult as well ? Obviously not, so what is the meaning of the colour coding ?


Which site belongs to which category ?


Why do we have the top 3 Twitter accounts listed and not the top 3 Youtube channels for instance ? What does it add to this viz and topic to know that Barack Obama is the most followed Twitter account ?


All this to say that the info here is difficult to interpret at first glance and requires effort to make sense of it.


I read the article (link above) that supports this chart. There we find the source and understand the numbers show the monthly visits.

Still no explanation of colour coding. I figured that companies belonging to the same group have the same colour and a link, except for grey that shows independent companies !

 

So now, how can we represent this better ?


I couldn't access the source from the visualisation above as it is paying data. So I looked for similar information on the net and found this page: https://ahrefs.com/blog/most-visited-websites/#most-visited-websites-global


I extracted the data from the table within the page to Tableau and made my own viz. For more info on how to do that, check out my article linked here.


A word of warning: the figures are different. That's because here I'm displaying the top websites per search traffic i.e. websites you've accessed from a search engine. Obviously, people rarely search for Google itself, therefore it's way below in this list.


But let's talk about the visualisation now.


First of all, these 2 charts are explaining clearly what they're talking about: the top 50 websites in terms of search traffic, per site category and parent company. The unit of measure is clear : monthly average billion visit. The source of data is immediately available.


2nd, with a bar chart it's easy to compare how each website relate to the others in terms of traffic. It's obvious that Youtube dwarves the competition and is twice as big as Facebook or Wikipedia. The sites are listed in decreasing order by monthly traffic, so #16 immediately follows #15.


Regarding the legend, I'm using the Tableau colour blind palette here. The bubble chart above was creating confusion with the website categories or why some bubbles have the same colour and are grouped together. That's because it's trying to display unrelated information on the same chart. Using 2 charts is removing that confusion.



Here's the same viz built in SAP Analytics cloud. Please not that SAC has integrated IBCS in its charts by default.




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Rosablanche

A BLOG ABOUT ANALYTICS & DATA
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